1 Introduction

This project delves into analyzing ransomware infections using data extracted from the Shodan API. By analyzing real-time data on internet-connected devices, we explore ransomware trends across various countries and cities. Through data visualizations and statistical analysis, we aim to identify geographic hotspots of ransomware activity, comprehend infection patterns, and provide valuable insights for cybersecurity professionals. The project underscores the importance of monitoring and comprehending ransomware incidents to enhance global cyber defenses.

1.1 Shodan API Overview

The Shodan API, a powerful tool for searching and retrieving data on internet-connected devices, provides information about devices’ locations, services, vulnerabilities, and more. In this project, the API is used to analyze global trends and patterns of ransomware infections.

2 Data Analysis of Ransomware Infections

This section analyzes ransomware infections. It starts with a summary of affected countries and reported incidents. A statistical analysis presents key metrics on infection distribution. The section concludes with a table detailing ransomware incidents by country and city, revealing geographic trends and high-infection areas.

2.1 Ransomware Infections Summary

According to the Shodan dataset, a total of 102 ransomware infections have been reported worldwide, impacting 38 countries. Brazil has the highest number of ransomware infections, reporting 12 incidents.

The city with the most ransomware infections is Frankfurt am Main, with 4 incidents.

2.1.1 Statistical Analysis

  • The average number of ransomware infections per country is 2.68.
  • The median number of ransomware infections per country is 1.
  • The standard deviation of ransomware infections per country is 2.79.

2.2 Table of Ransomware Infections by Country and City

This comprehensive table offers a detailed breakdown of ransomware infection rates across various countries and cities. It presents country and city names alongside the corresponding number of ransomware incidents, making it easy to compare regions. This table serves as a crucial reference point for understanding global ransomware trends and identifying areas where cyber defenses may need reinforcement.

Distribution of Ransomware Infections by Country and City
Country City Number of Infections
890 Germany Frankfurt am Main 4
1928 Russian Federation Moscow 3
2627 Brazil São Paulo 3
2669 China Shanghai 3
1138 United States Herndon 2
1288 Turkey Istanbul 2
1479 Ukraine Kyiv 2
1753 Brazil Manaus 2
2068 Germany Nürnberg 2
2253 Czechia Prague 2
2554 Chile Santiago 2
2605 Mexico Santiago de Querétaro 2
2707 China Shenzhen 2
2887 Uzbekistan Tashkent 2
36 United States Altamonte Springs 1
43 Brazil Aracruz 1
81 Brazil Araranguá 1
150 United States Ashburn 1
171 Kazakhstan Astana 1
222 Spain Barcelona 1
237 China Beijing 1
271 Brazil Boa Esperança 1
319 France Bourg-en-Bresse 1
346 Belarus Brest 1
414 Turkey Bursa 1
431 Egypt Cairo 1
463 Canada Calgary 1
503 China Chengdu 1
554 Moldova, Republic of Chisinau 1
579 China Chongqing 1
609 Argentina Comodoro Rivadavia 1
656 Colombia Cúcuta 1
720 United States Des Moines 1
725 Bangladesh Dhaka 1
776 Germany Düsseldorf 1
814 Germany Falkenstein 1
845 China Foshan 1
913 Argentina Godoy Cruz 1
955 Brazil Goiânia 1
1005 India Gurugram 1
1027 Argentina Haedo 1
1078 Finland Helsinki 1
1178 Viet Nam Ho Chi Minh City 1
1195 India Hyderābād 1
1240 Pakistan Islamabad 1
1297 Brazil Itajaí 1
1361 South Africa Johannesburg 1
1401 Taiwan Kaohsiung 1
1423 India Kolkata 1
1505 Nigeria Lagos 1
1556 United States Lee’s Summit 1
1583 Peru Lima 1
1623 Portugal Lisbon 1
1666 Spain Madrid 1
1706 Turkey Maltepe 1
1712 Bahrain Manama 1
1796 Colombia Manizales 1
1834 Colombia Medellín 1
1898 United States Mercerville 1
1955 India Mumbai 1
2004 Russian Federation Novyy Urengoy 1
2035 Mexico Nuevo Laredo 1
2108 Japan Osaka 1
2139 Czechia Ostrava 1
2178 Denmark Otterup 1
2225 Mexico Piedras Negras 1
2301 Mexico Puebla 1
2344 Poland Radom 1
2392 United States Rancho Santa Margarita 1
2418 Pakistan Rawalpindi 1
2437 Brazil Rio de Janeiro 1
2498 Russian Federation Saint Petersburg 1
2544 United States Santa Fe Springs 1
2766 Singapore Singapore 1
2780 Bulgaria Sofia 1
2848 United States Tacoma 1
2893 Brazil Toledo 1
2958 Spain Tortosa 1
2965 Argentina Villa Sarmiento 1
3034 Spain Villanueva de la Cañada 1
3060 Lithuania Vilnius 1
3108 Singapore Woodlands 1
3145 Serbia Zrenjanin 1

3 Data Visualization of Ransomware Infections

This section visualizes ransomware infection patterns globally. It maps incidents at country and city levels using Shodan API data, highlighting affected regions and trends. An interactive map lets users zoom in and examine infection details, making it useful for cybersecurity professionals and researchers.

3.1 Exploring Ransomware Hotspots

This data visualization explores the global distribution of ransomware infections, focusing on the geographical hotspots by country and city. Using data from the Shodan API, the map highlights areas with the highest concentrations of ransomware incidents, shedding light on trends and patterns in cyberattacks. By mapping ransomware infections based on real-time data, the visualization provides insights into which regions are most affected and allows for a better understanding of the geographic spread of these cyber threats. The interactive map enables users to zoom in on specific locations and view detailed information on the number of incidents, cities, and countries impacted, offering valuable insights for cybersecurity professionals and researchers.